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  70B still worth the pain
Posted by: vramforge - 10-11-2026, 05:49 AM - Forum: Proprietary / Frontier - No Replies

This keeps coming up in conversation so I figured I'd start a thread.

One thing I keep noticing is that people underestimate consumer GPUs until they actually try to run this stuff for more than one afternoon.

Maybe obvious to some of you, but it clicked for me this week.

For context, I'm not chasing leaderboard numbers. I mostly want the system to feel consistent day to day.

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  which local open model do you keep coming back to
Posted by: batchshed - 10-11-2026, 05:48 AM - Forum: Hosted - Replies (12)

Posting this in case it saves someone else a little time.

I'm helping a small team set up a local workflow. We don't need a giant stack, but we do care about continuous batching.

I'm especially interested in mistakes worth avoiding.

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  why did throughput drop after update for Kimi
Posted by: labpath - 10-11-2026, 05:35 AM - Forum: vLLM / SGLang - Replies (9)

I'm trying to sanity-check my setup.

I'm mostly working with Qwen in TensorRT-LLM on A6000. The part I'm trying to understand is speculative decoding.

Would appreciate practical advice rather than theory.

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  comparing models without fooling yourself with PyTorch
Posted by: kernelarch - 10-11-2026, 05:17 AM - Forum: Benchmarks - Replies (15)

This keeps coming up in conversation so I figured I'd start a thread.

The more I work with local setups, the more it seems like INT4 decides everything downstream.

Wondering if this is just where the whole space is heading now.

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  best local runtime for mixed models for Gemma
Posted by: fusedhall - 10-11-2026, 04:19 AM - Forum: Ollama / LM Studio / Desktop Runtimes - Replies (11)

Posting this in case it saves someone else a little time.

I'm helping a small team set up a local workflow. We don't need a giant stack, but we do care about small local stacks.

I'm especially interested in mistakes worth avoiding.

This is mostly for local work rather than public serving.

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  cleaning small domain dataset with llama.cpp
Posted by: routeline23 - 10-11-2026, 04:14 AM - Forum: Routers - Replies (1)

I'm trying to sanity-check my setup.

I'm mostly working with Mistral in Ollama on 5090. The part I'm trying to understand is HBM constraints.

If you've tested something similar, what did you keep and what did you stop bothering with?

I expected the biggest difference to come from the model, but the stack around it mattered at least as much.

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  70B still worth the pain
Posted by: cudapoint - 10-11-2026, 04:04 AM - Forum: Proprietary / Frontier - Replies (8)

Spent some time on this today and wanted to compare notes.

I'm comparing two approaches here: keep it simple on 5090, or squeeze more out of the stack and deal with the complexity.

What would you pick if you had to live with it for a few months?

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  latency vs throughput for small deployments for Llama
Posted by: localpatch78 - 10-11-2026, 03:34 AM - Forum: Performance Tuning - No Replies

Has anyone else run into this?

I'm trying to decide whether to keep the current stack or change course. Main question is how people here are handling router policy.

Not looking for the perfect answer, mostly what worked in real use.

If I had to summarize the lesson so far, it would be that clean setup and observability beat clever guesses.

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  70B still worth the pain: worth it?
Posted by: fastbench - 10-11-2026, 01:51 AM - Forum: Proprietary / Frontier - Replies (2)

I figured I'd ask here before changing everything.

I'm mostly working with Mistral in MLX on 4090. The part I'm trying to understand is KV cache pressure.

Would appreciate practical advice rather than theory.

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  quant choices for 70B local
Posted by: southden - 10-11-2026, 01:50 AM - Forum: Quantization - Replies (15)

Spent some time on this today and wanted to compare notes.

I'm comparing two approaches here: keep it simple on 7900 XTX, or squeeze more out of the stack and deal with the complexity.

What would you pick if you had to live with it for a few months?

This is mostly for local work rather than public serving.

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